Senior research associate
CMS Physics Analysis
Telephone: +43 (1) 51581 - 2813
Room: 3rd floor
- 2001 Diploma Thesis, "Towards 2D Quantum Gravity With Fermions", TU Wien
- 2001 Data scientist at HEPHY
- 2001 Joined CMS Collaboration, CERN
- 2004 PhD Thesis, "Development of Vertex Finding and Fitting Algorithms for CMS", TU Wien
- 2004 - 2008 PostDoc Position at HEPHY, working on b-tagging and vertexing for CMS, ILC
- 2008 Faculty position at HEPHY
- 2009 - 2012 Lead Vienna HEPHY Search Group for SUSY
- 2012 Founded SModelS collaboration
- 2014 Project Leader, "Interpretation of LHC Data with Simplified Models"
- 2015 Guest professor at Universidade de São Paolo
- 2018 "Venia docendi" at University of Vienna
- 2021/2022 Professeur invité at UGA / CNRS Grenoble
2014-2017: Austrian Science Fund Project P26896-N27, "Interpretation of LHC Data with Simplified Models"
2020-2023: Austrian Research Promotion Agency ML4CPD, "Machine Learning for Cryogenic Particle Detectors" (with Florian Reindl)
2022-2025: CERN technical PhD student programme, "Particle Shower Reconstruction in High Multiplicity Environments at the CMS
experiment" (with Erica Brondolin)
2022-2025: French-Austrian bilateral grant, I 5767, SLDNP "Statistically Learning Dispersed New Physics at the LHC" (with Sabine Kraml)
Lectures at TU Wien / Universität Wien:
- Winter 2015/2016
- 142.094, 260129, Lecture "Astro-particle physics", with Claudia Wulz
- Winter 2016/2017
- 142.094, 260129, Lecture "Astro-particle physics", with Manfred Jeitler
- Winter 2017/2018
- Summer 2018
- Lecture series, "Machine learning in particle physics", DKPI summer school
- Winter 2018/2019
- Winter 2019/2020
- 260032,142.340,142.351, Vorlesung und Übungen, "Statistische Methoden der Datenanalyse"
- Winter 2020/2021
- Winter 2021/2022
At HEPHY in Vienna I have started an analysis group that searches for signs of supersymmetry at CMS. In the last few years, though, I have focussed on the interpretation of the search results: given a positive or a null result, what are its implications? What do the data really tell us about supersymmetry, or other theories, and the question of naturalness?
To this end I founded a small collaboration, and together we developed "SModelS", a software framework that allows us to confront an arbitrary theoretical model with LHC results.
It is my ultimate vision that we can learn the fundamental physical laws beyond the Standard Model in an unsupervised fashion, employing modern machine learning techniques.
Also in data analysis I work at advancing novel machine learning techniques such as multi-level optimization, deep neural networks, and information geometry.
At times, my physics colleagues and I even manage to contribute back to the statistics and machine learning communites.
An older research interest of mine is the reconstruction of interaction vertices. This effort has resulted in the creation of a reconstruction toolkit "RAVE", that is currently in use in the Belle2 experiment.
- A complete list of my publications (>1000, as of january 2022) is here.
- h-Index: 108 (web of science, april 2022).
- My youtube lecture channel, a playlist with some of my talks and colloquia
Journal Publication (7)
- Ambrogi, Federico; Kraml, Sabine; Kulkarni, Suchita; Laa, Ursula; Lessa, Andre et al. [..] (2018) SModelS v1.1 user manual: Improving simplified model constraints with efficiency maps. Comput. Phys. Commun., Bd. 227, S. 72-98.
- Kraml, S.; Kulkarni, S.; Laa, U.; Lessa, A.; Magerl, W. et al. [..] (2014, online: 2014) SModelS: a tool for interpreting simplified-model results from the LHC and its application to supersymmetry. The European Physical Journal C, Bd. 74 (2014), S. 2868.
- Collaboration, CMS; Chatrchyan, S.; ..; Adam, W.; Aguilo, E. et al. [..] (2013) Interpretation of searches for supersymmetry with simplified models. Physical Review D, Bd. 88 (2013), S. 052017.
- Alves, D.; Arkani-Hamed, N.; Sanjay, A.; ..; Waltenberger, W. et al. [..] (2012) Simplified models for LHC new physics searches. Journal of Physics G, Bd. 39, S. 105005.
- Waltenberger, W. (2011) RAVE - a detector-independent toolkit toreconstruct vertices. IEEE Transactions on Nuclear Science (58 (2011)), S. 434-444.
- Waltenberger, W.; Frühwirth, R.; Vanlaer, P. (2007) Adaptive vertex fitting. Journal of Physics G, Bd. N343-N356 (Nucl. Part. Phys. 34), S. 18.
- Speer, T.; Frühwirth, R.; Vanlaer, P.; Waltenberger, W. (2006) Robust vertex fitters. Nuclear Instruments and Methods in Physics Research A, Bd. 566, S. 149 - 152.
Research Report (2)
- Kraml, S.; Kulkarni, S.; Laa, U.; Lessa, A.; Magerl, V. et al. [..] (2014) SModelS v1.0: a short user guide. Bericht-Nr. HEPHY-PUB-945-14, LPSC13295, arXiv:1412.1745;.
- Waltenberger, W. (2008) Adaptive Vertex Reconstruction. Bericht-Nr. CMS Note 2008/033; CERN:.